Xavier Tordoir

Xavier started his career as a researcher in Experimental Physics, and also focused on data processing. Further down the road, he took part in projects in finance, genomics, and software development for academic research. During that time, he worked on timeseries, on the prediction of biological molecular structures and interactions, and applied Machine Learning methodologies. He developed solutions to manage and process data distributed across data centres. He founded and now works at Data Fellas, a company dedicated to distributed computing and advanced analytics, leveraging Scala, Spark, and other distributed technologies.

Talks I've Given

Get your hands dirty with distributed tools, during these two hours we’ll have a quick overview on how a dataset can be processed in a distributed way towards the exposition exposition as a web service.

The tool we’ll use for this are Spark, Cassandra, Akka HTTP and the Spark Notebook.

While machine learning has been used for decades, accessibility to these methods is undergoing a radical shift, with the rise of simple interfaces and implementations on distributed systems. In practice it means that more players can afford to take advantage of Machine Learning, and at larger...